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Anthropic vs Deepset

Anthropic scores higher on the AgentReady, 80/100 against 44/100. They differ on 6 of the 41 signals. Which ones decides whether an agent can adopt them without a person watching.

What each one is

Anthropic. Anthropic is a public benefit corporation dedicated to securing the benefits of AI and mitigating its risks.

Deepset. Deepset is a company that provides Haystack, an open platform to build, run, and govern AI agents and applications.

Where Anthropic is ahead

Anthropic passes authentication documented, and Deepset does not. That is understand, whether an agent can read the docs and work out how the API behaves before calling it.

It also holds operate: agent compatibility verified. Deepset misses it.

Where Deepset is ahead

Deepset passes search discoverable, and Anthropic does not. That is discover, whether an agent can find the product at all without being told it exists.

It also holds adopt: official python sdk. Anthropic misses it.

And on operate, canonical workflow succeeds and observable execution. Anthropic misses those.

What neither does

Both fail clear product positioning, public docs discoverable, llms-full.txt / full agent docs, structured api reference, openapi / spec quality, request examples provided, response examples provided, errors and status codes documented, limits / constraints documented, no mandatory sales call, programmatic credential creation, fast time to first request, copyable quickstart, official typescript sdk, structured, predictable output, machine-readable errors, retry behavior documented, idempotency support, rate-limit behavior predictable. If your agent needs any of those, you will be building it yourself either way.

Score, pillar by pillar

The AgentReady splits into four pillars, scored separately, because a product can be easy to find and still impossible to adopt.

Discover. Both sit at 67/100 here. Anthropic misses search discoverable, clear product positioning, public docs discoverable, llms-full.txt / full agent docs; Deepset misses clear product positioning, public docs discoverable, llms-full.txt / full agent docs.

Understand. Anthropic leads 75 to 23. Anthropic misses structured api reference, openapi / spec quality, request examples provided, response examples provided, errors and status codes documented, limits / constraints documented; Deepset misses structured api reference, openapi / spec quality, authentication documented, request examples provided, response examples provided, errors and status codes documented, limits / constraints documented.

Adopt. Anthropic leads 88 to 50. Anthropic misses no mandatory sales call, programmatic credential creation, fast time to first request, copyable quickstart, official typescript sdk, official python sdk; Deepset misses no mandatory sales call, agent-compatible signup flow, programmatic credential creation, fast time to first request, copyable quickstart, official typescript sdk.

Operate is whether an agent can run against it in production and recover when a call fails. Anthropic leads 89 to 35. Anthropic misses canonical workflow succeeds, structured, predictable output, machine-readable errors, retry behavior documented, idempotency support, rate-limit behavior predictable, observable execution; Deepset misses structured, predictable output, machine-readable errors, retry behavior documented, idempotency support, rate-limit behavior predictable, agent compatibility verified.

Pricing

Anthropic does not publish a machine-readable starting price and has a free tier. Deepset starts at $0/mo and has a free tier.

Signal by signal

Which to pick

Deepset clears more of the signals an agent needs, so it is the safer default for unattended use. Full profiles: Anthropic and Deepset. Alternatives to each: Anthropic, Deepset.

An agent can fetch this as data: POST /v1/compare {"slugs": ["anthropic", "deepset"]}